Field of the Invention
This disclosure relates generally to signal analysis and more specifically to the detection of a repetition within a signal.
Description of Art
Sensors, such as accelerometers, can be used to generate signals of physical motion, which can include repetitive motion. Repetitions can be described as periodic transitions from one state for another. For example, if a signal represents a person performing push-up exercises, the repetitions can represent the user transitioning from a position with their arms straight to a position with their arms bent and then back to the first, straight-arm position. These repetitions can be represented by cycles in periodic curves within the signals, such as sinusoids and Fourier series.
The detection of repetitions within signals of real world data is conventionally difficult because the signals can contain noise that obscures the repetitions in the signal. For example, a signal of the person performing the push-ups can be made noisy by the person shaking, inaccuracies in a sensor capturing the push-up motion, or by the person's inconsistency in performing the push-ups. Thus, simply locating local extrema within the signal can be inaccurate, especially in situations where multiple repetitions are not performed continuously, since the extrema may not exist in the signal in these cases.
The difficulty in identifying repetitions within a signal impacts exercise assistance systems, which automatically provide exercise advice and guidance to users. By being unable to identify repetitions in signals describing user movement, conventional exercise assistance systems often can only provide general guidance that does not address the particularities of an individual user's performance of an exercise.